As with all major releases, PostgreSQL 11 includes bug fixes and is full of performance changes; but, if there were a theme to this latest release, it would center around improved handling of large-scale data.

In this post, we’ll take a look at some of the more noteworthy improvements around partitioning and queries, and how they make Postgres even more powerful for use cases with large data sets.

Noteworthy updates to PostgreSQL 11

1. Improved partitioning

Partition elimination has been greatly enhanced, providing even quicker access to tables with multiple partitions and opening it up to query execution. Additionally, some tasks are now automated, such as updated rows moving to new partitions based on the row contents.

2. Parallel queries

PostgreSQL 11 comes with many improvements to parallelization, including what can be parallelized and parallel worker configuration. For example, you can now build btree indexes in parallel and parallelize certain queries.

3. Just-in-Time compilation

A powerful way to increase the execution speed through making some expressions into natively executed functions by the CPU, Just-in-Time compilation has been expanded to include support for additional SQL code and parts of query plans.

Wrapping up

PostgreSQL 11 continues to improve PG’s scalability by improving partitioning and parallel queries, and expanding Just-in-Time compilation. These improvements will result in greater speed and resource management.

Coupled with Aiven features like local SSDs, Aiven users will get even greater performance from PostgreSQL 11. If you’re an Aiven user, get the latest version by simply performing an in-place upgrade within the console. Not an Aiven user?

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